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We are looking for a strategic product leader to own Skills Intelligence and Learning Experiences at Degreed: the intelligence layer that defines what a skill is and how proficiency is measured, and the learning experiences that turn that intelligence into real capability growth.

This role is built for a product manager who has shipped learning platforms at scale and knows what it takes to help people actually learn. You understand the difference between content a learner clicks through and a program that changes what someone can do. You have built the systems that recommend the next right thing, structure a path toward a goal, and demonstrate that a skill was developed rather than simply consumed. Learner outcomes are the point, and you keep them at the center of every decision.

Underneath those experiences sits Degreed's skills data model: the foundation that defines what a skill is, how proficiency is measured, and how that information powers AI, learning experiences, and enterprise workflows across the product. You will own that foundation as well, and you will treat it as a long-lived system rather than a collection of features. Success comes from a skills model that becomes more useful over time, supports new products without constant rework, and gives customers confidence that the data behind it can be trusted.

The role owns both halves of the loop: the intelligence that makes learning relevant, and the learning experiences where learners discover, develop, and demonstrate new skills. The strongest candidate is fluent in both and insists that neither works without the other.

• Learning product leadership. You have shipped learning platforms or learning products that measurably helped people build skills, and you can point to the outcomes, not just the launches. You lead with both the learner and the enterprise buyer in mind, and you translate each into product decisions.
• Enterprise learning fluency. You understand how large organizations structure learning: academies, certifications, career paths, and cohort-based programs. You can translate those models into product decisions that hold up across very different customers.
• Assessment design. You can define proficiency scales with clear, observable distinctions between levels, and explain those distinctions to customers when challenged. A background in psychometrics or learning assessment is a strong advantage.
• Taxonomy design depth. You have built classification systems that stay useful as domains evolve. You are familiar with frameworks such as O*NET and ESCO, and you understand how AI-based skill matching depends on taxonomy quality.
• Data product mindset. You have managed structured data with clear ownership, versioning, quality standards, and well-defined interfaces for downstream consumers.
• Long-term systems thinking. You design systems that grow more accurate and useful as data accumulates, and you define the metrics that prove that improvement.
• ML fluency. You understand enough about how ML models consume training data to work effectively with engineers and to evaluate data quality, coverage, and sources of bias.
• Trust and fairness judgment. You are comfortable in ambiguous situations where standardized definitions and customer requirements do not fully align. You make consistent decisions and explain the reasoning behind them.
• AI-assisted workflows. You use AI to accelerate taxonomy research, synthesize across sources, and prototype changes before implementation.
  

Learning Experiences

• Shape Degreed's learning experiences, from self-paced pathways to structured, cohort-based programs.
• Own Degreed Academies, enabling enterprise customers to deliver certifications, onboarding, and other structured learning programs.
• Decide how skill data powers personalized learning recommendations, including what content gets suggested to a learner next.
• Direct the AI feature that identifies a learner's skill gaps and generates content to close them.
• Design the full learner journey: how someone finds a skill gap, engages with content, and demonstrates they have closed it.

Skills Intelligence

• Own the full data model behind Degreed's skills product: how skills are defined, organized, and kept accurate as the system grows.
• Run the platform enterprise clients use to adapt Degreed's skill list to their own internal language, combining AI suggestions with human review.
• Design the rating scale used to measure skill proficiency, including the criteria that separate one level from the next.
• Keep Degreed's skill data compatible with external frameworks and with enterprise HR systems.
• Build the process by which every AI interaction across the product improves the underlying skill data over time, and measure that improvement with real numbers.
• Evolve the skills model by making deliberate trade-offs between consistency, customer flexibility, and long-term product health.
  

• Experience level: Expert (8+ years), including direct ownership of shipped learning products.